Antiangiogenic therapy is emerging as a major tumor treatment modality. Owing to dynamical and temporal effects in endothelial-tumor interactions, tumor response to such therapy depends in a complicated manner on dose and dose-timing, for one drug or several. The many options available suggest the need to help rationalize antiangiogenic treatment planning, which is in its early stages, by quantitative modeling. The grant addresses these concerns, combining experiments with biomathematics. The theoretical arm will extend a dynamic carrying capacity model for endothelial-tumor interactions and response to antiangiogenic treatment, which was developed and applied under the current grant. This biologically based differential equation model, involving only a minimal number of adjustable parameters, is implemented with computer algorithms. Experimentally, we will analyze tumor size data for animal studies already ongoing at the Folkman laboratory, and use state-of-the-art imaging of vasculature response to antiangiogenic treatment. Specifically: (1) our dynamic carrying capacity model predicted that smoothing out delivery of an antiangiogenic drug in time can lead to improved tumor response. Data, both published and from our laboratory, show that the effect often does occur. The PI hypothesizes that this observed effect basically derives from resensitization, a known phenomenon for various kinds of treatment, predicted by various models. In the new grant we will study dose-timing effects more closely, and extend the model to study additional resensitization effects that can occur due to diversity among endothelial cells. (2) We will also use the model to understand and anticipate antiangiogenic dose-response and drug combination effects. The model and experiments have already shown that complex tumor responses, such as apparent synergism when two antiangiogenic agents are combined, can result even when the underlying action on the time rate of change of the endothelial target is linear. (3) We will corroborate the predicted correlated dynamical responses of tumor and endothelium with the help of digitized automated imaging of intratumor vasculature in serial sections, supplied by the Folkman laboratory, for treated and control human tumors grown as mouse xenografts. Quantitative modeling is proposed as a relatively inexpensive and rapid way to help bridge the gap between experiments and clinical implementations for dose, dose-timing, and inhibitor combinations.